Current Air Traffic Management (ATM) Systems are being developed according to an approach focused on increasing capacity, efficiency and safety, while reducing environmental impact. These objectives require a paradigm shift from a system that manages aerospace based on tactical intervention by human operators to a more strategic, integrated and collaborative system that relies on coordinated and strategic trajectory de-confliction supported by advanced automation tools. According to the new paradigm, the aircraft trajectory becomes the centerpiece of a new set of operating procedures collectively referred to as Trajectory Based Operations (TBO).
TBO is the subject of extensive investigation worldwide within the course of the major ATM modernization and UAS (Unmanned Aerial Systems) insertion initiatives, where it is recognized that novel methods to define and predict aircraft trajectories with higher fidelity and accuracy are needed along with advanced tools to enable their computational treatment to facilitate the introduction of higher levels of automation and autonomy in air vehicle operations.
Aircraft Intent Description Language (AIDL) is a first attempt to define aircraft trajectories unambiguously. When defining and executing air vehicle trajectories defined by using AIDL, six functions can be acknowledged: a) Trajectory Modeling; b) Intent Generation; c) Intent Inference; d) Trajectory Prediction; e) Flight Control; and 0 State Estimation.
Trajectory Modeling includes planning, editing and visualizing intended aircraft trajectories, using Aircraft Intents (AI), which unequivocally define a precise way an air vehicle is to be operated. In other words, by use of an AI-based Trajectory Modeling, a precise a priori definition of aircraft guidance strategy and aircraft motion is achieved, thus precisely defining an aircraft trajectory.
Intent Generation includes finding a determinate AI that satisfies a given constraint or a given set of constraints to which the desired aircraft trajectory must be restricted.
Intent Inference includes discovering (inferring) the most likely AI that gave rise to (e.g., that affected) a known aircraft trajectory through reverse engineering from observations of its geometry and timing (e.g., from radar tracks, telemetry data or recorded navigation data).
Trajectory Prediction includes determining (predicting) an aircraft trajectory that results from a given instance of AI based on models of the aircraft performance and the atmospheric conditions (pressure, temperature and wind) in which the flight takes place.
Flight Control includes automatically and precisely executing a given instance of AI.
State Estimation includes making use of the precise information included within an AI instance to find air vehicle state information at a certain point along its trajectory.
After several years of investigation in the field of ATM systems, many problems have been found that are worth being addressed. The first of these problems refers to a lack of a common shared data structure to handle aircraft instances in AIDL. The abovementioned functions related to ATM are typically tackled by use of modules which either produce or consume AIDL instances. Thus, there is a need to develop a common AIDL data structure for defining aircraft trajectories, for the different modules involved in air vehicle trajectory definition and execution to take advantage thereof.
Another problem concerning ATM systems can be regarded as a lack of unified interface to address all of the abovementioned functions. An additional problem refers to a lack of standard encoding for the AI instances. It would be desirable to develop a standard way in which to encode and serialize AIDL instances. Another problem that can be observed when facing trajectory definition and execution using AIDL refers to the validation of AI instances. Because AIDL is a formal language, there must be a series of lexical and syntactical rules that should be validated to ensure that a determinate AI instance makes sense or satisfactorily fulfils the requirements established by the user or ATM system manager.